Linganisha mbinu

	Usajili wa Kuishi	Rega ya Hatari za Uwiano wa Cox
Nyanja	Takwimu	Uchanganuzi wa Uhai
Familia	Regression model	Survival analysis
Mwaka wa asili	1980s	1972
Mwanzilishi	Kalbfleisch & Prentice; Cox & Oakes	Cox, D. R.
Aina	Parametric survival model	Semi-parametric hazard regression model
Chanzo asilia	Kalbfleisch, J. D., & Prentice, R. L. (2002). The Statistical Analysis of Failure Time Data (2nd ed.). Wiley. ISBN: 978-0471363576	Cox, D. R. (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202.
Majina mbadala	accelerated failure time model, AFT model, parametric survival model, time-to-event regression	cox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu
Zinazohusiana	3	3
Muhtasari	Survival regression models the time until an event occurs — such as death, failure, or relapse — as a function of covariates. Unlike ordinary regression, it properly accounts for censored observations (cases where the event had not yet occurred at the end of follow-up) by specifying a parametric distribution for the survival time and estimating covariate effects via maximum likelihood.	Cox proportional hazards regression, introduced by D. R. Cox in 1972, is a semi-parametric model that estimates how one or more covariates affect the hazard — the instantaneous rate of experiencing an event — while leaving the baseline hazard function unspecified. It is the standard multivariable method in survival analysis and produces hazard ratios that quantify the relative risk associated with each predictor.